DataBytes-Organisation/Intelligent-IoT-Data-Management
Apr 2026 – May 2026
2 Months active
Languages Used
Python
Technical Skills
Pythonanomaly detectiondata analysisdata sciencemachine learningPython scripting
Bhavesh Choudhary
PROFILE
Bhavesh Choudhary
Worked on the DataBytes-Organisation/Intelligent-IoT-Data-Management repository to enhance time-series anomaly detection capabilities in IoT data streams. Developed and integrated the QuantileAD anomaly detector into the existing Python-based pipeline, benchmarking its performance and improving early anomaly identification. Overhauled the anomaly detection pipeline by adding support for ECOD and COPOD detectors, enabling comprehensive benchmarking and evaluation using metrics such as ROC-AUC, precision, recall, and F1. Improved code maintainability through repository housekeeping, including .gitignore updates and removal of unnecessary files. Leveraged Python, pandas, and machine learning techniques to deliver a reproducible, maintainable, and extensible data science workflow for anomaly detection.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
14Total
Bugs
0
Commits
14
Features
4
Lines of code
2,347
Activity Months2
Your Network
25 peopleShared Repositories
25
Work History
May 2026
13 Commits • 3 Features
May 1, 2026Concise monthly summary for 2026-05 focusing on key accomplishments, top achievements, impact, and technologies demonstrated. Highlights include a major overhaul of the anomaly detection pipeline with QuantileAD integration, lifecycle integration of ECOD and COPOD detectors, and repository housekeeping to improve maintainability.
13 Commits • 3 Features
May 1, 2026Concise monthly summary for 2026-05 focusing on key accomplishments, top achievements, impact, and technologies demonstrated. Highlights include a major overhaul of the anomaly detection pipeline with QuantileAD integration, lifecycle integration of ECOD and COPOD detectors, and repository housekeeping to improve maintainability.
May 2026
April 2026
1 Commits • 1 Features
Apr 1, 2026April 2026 monthly summary for DataBytes-Organisation/Intelligent-IoT-Data-Management: Implemented QuantileAD anomaly detector in the time-series data processing pipeline, integrated into the system, with benchmarking to validate performance gains. This delivery improves anomaly detection accuracy, enabling proactive maintenance and higher data quality across IoT streams. No major bugs reported this month; focus was on feature delivery, integration, and validation.
April 2026
1 Commits • 1 Features
Apr 1, 2026April 2026 monthly summary for DataBytes-Organisation/Intelligent-IoT-Data-Management: Implemented QuantileAD anomaly detector in the time-series data processing pipeline, integrated into the system, with benchmarking to validate performance gains. This delivery improves anomaly detection accuracy, enabling proactive maintenance and higher data quality across IoT streams. No major bugs reported this month; focus was on feature delivery, integration, and validation.
Activity
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Quality Metrics
Correctness91.4%
Maintainability82.8%
Architecture85.8%
Performance82.8%
AI Usage32.8%
Skills & Technologies
Programming Languages
Python
Technical Skills
PythonPython scriptinganomaly detectiondata analysisdata sciencedata visualizationgitmachine learningpandas
Repositories Contributed To
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